Chapter 1 Introduction
Overview
Data Science Is OSEMN
Intermezzo Chapters
What Is the Command Line?
Why Data Science at the Command Line?
A Real-World Use Case
Further Reading
Chapter 2 Getting Started
Overview
Setting Up Your Data Science Toolbox
Essential Concepts and Tools
Further Reading
Chapter 3 Obtaining Data
Overview
Copying Local Files to the Data Science Toolbox
Decompressing Files
Converting Microsoft Excel Spreadsheets
Querying Relational Databases
Downloading from the Internet
Calling Web APIs
Further Reading
Chapter 4 Creating Reusable Command-Line Tools
Overview
Converting One-Liners into Shell Scripts
Creating Command-Line Tools with Python and R
Further Reading
Chapter 5 Scrubbing Data
Overview
Common Scrub Operations for Plain Text
Working with CSV
Working with HTML/XML and JSON
Common Scrub Operations for CSV
Further Reading
Chapter 6 Managing Your Data Workflow
Overview
Introducing Drake
Installing Drake
Obtain Top Ebooks from Project Gutenberg
Every Workflow Starts with a Single Step
Well, That Depends
Rebuilding Specific Targets
Discussion
Further Reading
Chapter 7 Exploring Data
Overview
Inspecting Data and Its Properties
Computing Descriptive Statistics
Creating Visualizations
Further Reading
Chapter 8 Parallel Pipelines
Overview
Serial Processing
Parallel Processing
Distributed Processing
Discussion
Further Reading
Chapter 9 Modeling Data
Overview
More Wine, Please!
Dimensionality Reduction with Tapkee
Clustering with Weka
Regression with SciKit-Learn Laboratory
Classification with BigML
Further Reading
Chapter 10 Conclusion
Let’s Recap
Three Pieces of Advice
Where to Go from Here?
Getting in Touch